ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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Dmitri Smirnov 1e18efade5
[C#] Add ML Sequences and Maps Create and Process APIs (#16648)
### Description
1) Added Sequence And Maps convenience APIs to create input Sequences
and Maps
and also visit the outputs.

2) Address OrtValue design issue when the values are created on top of
the
managed memory and the ortValues are used for sequence and maps
creation.
We should retain the original managed instances that keep the memory
pinned.
We opt to keep track of those and dispose of them within an instance of
OrtValue
that represents a Map or a Sequence.

3) Set `LangVersion` to default per [MS Versioning
Docs.](https://learn.microsoft.com/en-us/dotnet/csharp/language-reference/configure-language-version)

### Motivation and Context
1) When writing code examples, use of Map and Sequences API proved to be
cumbersome.
2) It is a BUG, that we should address, as the managed memory can move
by the GC and lead to
intermittent crashes.
3) Make use of the most feature of the C#.
2023-07-21 12:58:29 +08:00
.config
.devcontainer
.gdn Update win-ci-pipeline.yml: enable xnnpack tests (#16244) 2023-06-14 19:12:42 -07:00
.github Bump actions/checkout from 2 to 3 (#16405) 2023-07-01 03:51:31 +00:00
.pipelines [DML EP] Update DirectML version to 1.12.0 (#16011) 2023-05-18 19:37:12 -07:00
.vscode
cgmanifests [TensorRT EP] TRT 8.6 minor version update (#16475) 2023-06-26 10:44:27 -07:00
cmake [ROCm][MIGraphX] for googletest dep, set OVERRIDE_FIND_PACKAGE (#16715) 2023-07-21 00:57:38 +08:00
csharp [C#] Add ML Sequences and Maps Create and Process APIs (#16648) 2023-07-21 12:58:29 +08:00
dockerfiles Enable model subgraph execution in OVEP and setting the OpenVINO dll's to the path from the OpenVINO pypi packge in OVEP and fix OVEP windows io buffer sample (#16147) 2023-06-16 19:47:09 -07:00
docs ovep dockerfile and wheel docs changes (#16482) 2023-07-19 09:01:09 -07:00
include/onnxruntime/core Fix bug with saving model optimized by inference session (#16716) 2023-07-20 18:44:28 -07:00
java [java] Adding addExternalInitializers and addInitializer to OrtSession.SessionOptions (#16198) 2023-07-05 12:51:59 -07:00
js [js/web] upgrade onnx-proto version (#16722) 2023-07-18 16:36:39 -07:00
objectivec Objective-C Add Support to Create and Query String ORTValues (#16764) 2023-07-20 17:39:29 -07:00
onnxruntime [QNN EP] Op support: LayerNorm, Asin, Sign (#16740) 2023-07-20 20:57:48 -07:00
orttraining Replace call to deprecated torch.norm (#16758) 2023-07-20 19:52:19 -07:00
rust
samples Enable pylint and numpy rules (#15218) 2023-03-27 20:37:53 -07:00
swift/OnnxRuntimeBindingsTests Add iOS Swift Package Manager support (#15297) 2023-04-20 16:18:35 +10:00
tools Objective-C Add Support to Create and Query String ORTValues (#16764) 2023-07-20 17:39:29 -07:00
winml [WinML] Fix warnings in OnnxruntimeEngine and OnnxruntimeEngineBuilder (#16679) 2023-07-12 13:09:50 -07:00
.clang-format Run clang-format in CI (#15524) 2023-04-18 09:26:58 -07:00
.clang-tidy
.dockerignore
.gitattributes
.gitignore remove 'lib/' from .gitignore (#15613) 2023-04-24 18:43:32 -07:00
.gitmodules Update eigen to 3.4 and remove the eigen from git submodule (#15875) 2023-05-11 11:56:59 -07:00
.lintrunner.toml Minimal Build for On-Device Training (#16326) 2023-06-22 12:27:23 -07:00
build.bat Upgrade old Python version in packaging pipeline (#16667) 2023-07-17 08:24:47 -07:00
build.sh Upgrade old Python version in packaging pipeline (#16667) 2023-07-17 08:24:47 -07:00
CITATION.cff
CODEOWNERS Add owners for public facing API files (#15288) 2023-03-30 17:16:15 -07:00
CONTRIBUTING.md
lgtm.yml
LICENSE
NuGet.config
ort.wprp
ORT_icon_for_light_bg.png
Package.swift Objective-C Add Support to Create and Query String ORTValues (#16764) 2023-07-20 17:39:29 -07:00
packages.config [DML EP] Update DirectML version to 1.12.0 (#16011) 2023-05-18 19:37:12 -07:00
pyproject.toml Bump ruff in CI (#15533) 2023-04-17 10:11:44 -07:00
README.md add third-party pipeline status to README.md (#16155) 2023-05-31 22:14:39 -07:00
requirements-dev.txt Remove codecov from requirements-dev.txt (#15487) 2023-04-12 18:48:02 -07:00
requirements-doc.txt
requirements-lintrunner.txt Enable RUFF as a formatter (#15699) 2023-04-26 14:04:07 -07:00
requirements-training.txt
requirements.txt.in
SECURITY.md
setup.py Triton Codegen for ORTModule (#15831) 2023-07-13 18:17:58 +08:00
ThirdPartyNotices.txt Implement openAI endpoint invoker for nuget (#15797) 2023-05-11 22:04:02 -07:00
VERSION_NUMBER Update VERSION_NUMBER (#15773) 2023-05-03 15:07:34 -07:00

ONNX Runtime is a cross-platform inference and training machine-learning accelerator.

ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. Learn more →

ONNX Runtime training can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. Learn more →

Get Started & Resources

Builtin Pipeline Status

System Inference Training
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Third-party Pipeline Status

System Inference Training
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Data/Telemetry

Windows distributions of this project may collect usage data and send it to Microsoft to help improve our products and services. See the privacy statement for more details.

Contributions and Feedback

We welcome contributions! Please see the contribution guidelines.

For feature requests or bug reports, please file a GitHub Issue.

For general discussion or questions, please use GitHub Discussions.

Code of Conduct

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

License

This project is licensed under the MIT License.